Mashup services to daily activities: end-user perspective in designing a consumer mashups. - Zhenzhen Zhao; Sirsha Bhattarai; Ji Liu 003; Noël Crespi (iiWAS, 2011)

The design of activity-oriented social networking: Dig-Event. - Zhenzhen Zhao; Ji Liu 003; Noël Crespi (iiWAS, 2011)

Dig-event: let's socialize around events. - Zhenzhen Zhao; Ji Liu 003; Noël Crespi (CSCW (Companion), 2012)

Scientific Workflow Partitioning in Multisite Cloud. - Ji Liu 003; Vítor Silva 003; Esther Pacitti; Patrick Valduriez; Marta Mattoso (Euro-Par Workshops (1), 2014)

A Survey of Data-Intensive Scientific Workflow Management. - Ji Liu 003; Esther Pacitti; Patrick Valduriez; Marta Mattoso (J. Grid Comput., 2015)

Managing hot metadata for scientific workflows on multisite clouds. - Luis Pineda-Morales; Ji Liu 003; Alexandru Costan; Esther Pacitti; Gabriel Antoniu; Patrick Valduriez; Marta Mattoso (IEEE BigData, 2016)

Scientific Workflow Scheduling with Provenance Support in Multisite Cloud. - Ji Liu 003; Esther Pacitti; Patrick Valduriez; Marta Mattoso (VECPAR, 2016)

Multi-objective scheduling of Scientific Workflows in multisite clouds. - Ji Liu 003; Esther Pacitti; Patrick Valduriez; Daniel de Oliveira 001; Marta Mattoso (Future Gener. Comput. Syst., 2016)

Multisite Management of Scientific Workflows in the Cloud. (Gestion multisite de workflows scientifiques dans le cloud). - Ji Liu 003 (2016)

Scientific Workflow Scheduling with Provenance Data in a Multisite Cloud. - Ji Liu 003; Esther Pacitti; Patrick Valduriez; Marta Mattoso (Trans. Large Scale Data Knowl. Centered Syst., 2017)

Computation of PDFs on Big Spatial Data: Problem & Architecture. - Ji Liu 003; Noel Moreno Lemus; Esther Pacitti; Fábio Porto 001; Patrick Valduriez (LADaS@VLDB, 2018)

Scientific Data Analysis Using Data-Intensive Scalable Computing: The SciDISC Project. - Patrick Valduriez; Marta Mattoso; Reza Akbarinia; Heraldo Borges; José J. Camata; Alvaro L. G. A. Coutinho; Daniel Gaspar; Noel Moreno Lemus; Ji Liu 003; Hermano Lustosa; Florent Masseglia; Fabrício Nogueira da Silva; et al. (LADaS@VLDB, 2018)

A survey of scheduling frameworks in big data systems. - Ji Liu 003; Esther Pacitti; Patrick Valduriez (Int. J. Cloud Comput., 2018)

Efficient Scheduling of Scientific Workflows Using Hot Metadata in a Multisite Cloud. - Ji Liu 003; Luis Pineda-Morales; Esther Pacitti; Alexandru Costan; Patrick Valduriez; Gabriel Antoniu; Marta Mattoso (IEEE Trans. Knowl. Data Eng., 2019)

Data-Intensive Workflow Management: For Clouds and Data-Intensive and Scalable Computing Environments - Daniel C. M. de Oliveira; Ji Liu 003; Esther Pacitti (Data-Intensive Workflow Management, 2019)

Quasi-optimal Data Placement for Secure Multi-tenant Data Federation on the Cloud. - Qi Kang; Ji Liu 003; Sijia Yang; Haoyi Xiong; Haozhe An; Xingjian Li 002; Zhi Feng; Licheng Wang; Dejing Dou (IEEE BigData, 2020)

An Investigation of Containment Measures Against the COVID-19 Pandemic in Mainland China. - Ji Liu 003; Xiakai Wang; Haoyi Xiong; Jizhou Huang; Siyu Huang; Haozhe An; Dejing Dou; Haifeng Wang 001 (IEEE BigData, 2020)

SUQ2: Uncertainty Quantification Queries over Large Spatio-temporal Simulations. - Noel Moreno Lemus; Fábio Porto 001; Yania Molina Souto; Rafael S. Pereira 001; Ji Liu 003; Esther Pacciti; Patrick Valduriez (IEEE Data Eng. Bull., 2020)

Parallel computation of PDFs on big spatial data using Spark. - Ji Liu 003; Noel Moreno Lemus; Esther Pacitti; Fábio Porto 001; Patrick Valduriez (Distributed Parallel Databases, 2020)

C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods Ahead of COVID-19 Outbreak. - Congxi Xiao; Jingbo Zhou; Jizhou Huang; An Zhuo; Ji Liu 003; Haoyi Xiong; Dejing Dou (AAAI, 2021)

Elastic Deep Learning Using Knowledge Distillation with Heterogeneous Computing Resources. - Daxiang Dong; Ji Liu 003; Xi Wang; Weibao Gong; An Qin 001; Xingjian Li 002; Dianhai Yu; Patrick Valduriez; Dejing Dou (Euro-Par Workshops, 2021)

An Investigation of Containment Measure Implementation and Public Responses to the COVID-19 Pandemic in Mainland China. - Ji Liu 003; Haoyi Xiong; Xiakai Wang; Jizhou Huang; Qiaojun Li; Tongtong Huang; Siyu Huang; Haifeng Wang 001; Dejing Dou (ICDH, 2021)

Evaluation and Optimization of learning-based DNS over HTTPS Traffic Classification. - Yue Li 011; Abdulhalim Dandoush; Ji Liu 003 (ISNCC, 2021)

MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal. - Weijia Zhang 003; Hao Liu 026; Lijun Zha; Hengshu Zhu; Ji Liu 003; Dejing Dou; Hui Xiong 001 (KDD, 2021)

Validating the Lottery Ticket Hypothesis with Inertial Manifold Theory. - Zeru Zhang; Jiayin Jin; Zijie Zhang 001; Yang Zhou 001; Xin Zhao; Jiaxiang Ren 001; Ji Liu 003; Lingfei Wu 001; Ruoming Jin; Dejing Dou (NeurIPS, 2021)

Interpretable Deep Learning: Interpretations, Interpretability, Trustworthiness, and Beyond. - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xuanyu Wu; Xiao Zhang 001; Ji Liu 003; Jiang Bian 003; Dejing Dou (CoRR, 2021)

HeterPS: Distributed Deep Learning With Reinforcement Learning Based Scheduling in Heterogeneous Environments. - Ji Liu 003; Zhihua Wu; Dianhai Yu; Yanjun Ma; Danlei Feng; Minxu Zhang; Xinxuan Wu; Xuefeng Yao; Dejing Dou (CoRR, 2021)

Improving Adversarial Robustness via Attention and Adversarial Logit Pairing. - Xingjian Li 002; Dou Goodman; Ji Liu 003; Tao Wei; Dejing Dou (Frontiers Artif. Intell., 2021)

AgFlow: fast model selection of penalized PCA via implicit regularization effects of gradient flow. - Haiyan Jiang; Haoyi Xiong; Dongrui Wu; Ji Liu 003; Dejing Dou (Mach. Learn., 2021)

Efficient Device Scheduling with Multi-Job Federated Learning. - Chendi Zhou; Ji Liu 003; Juncheng Jia; Jingbo Zhou; Yang Zhou 001; Huaiyu Dai; Dejing Dou (AAAI, 2022)

Energy Efficient, Real-time and Reliable Task Deployment on NoC-based Multicores with DVFS. - Lei Mo; Qi Zhou; Angeliki Kritikakou; Ji Liu 003 (DATE, 2022)

Federated Fingerprint Learning with Heterogeneous Architectures. - Tianshi Che; Zijie Zhang 001; Yang Zhou 001; Xin Zhao; Ji Liu 003; Zhe Jiang 001; Da Yan 001; Ruoming Jin; Dejing Dou (ICDM, 2022)

Accelerated Federated Learning with Decoupled Adaptive Optimization. - Jiayin Jin; Jiaxiang Ren 001; Yang Zhou 001; Lingjuan Lyu; Ji Liu 003; Dejing Dou (ICML, 2022)

FedHiSyn: A Hierarchical Synchronous Federated Learning Framework for Resource and Data Heterogeneity. - Guanghao Li; Yue Hu; Miao Zhang; Ji Liu 003; Quanjun Yin; Yong Peng 006; Dejing Dou (ICPP, 2022)

FedDUAP: Federated Learning with Dynamic Update and Adaptive Pruning Using Shared Data on the Server. - Hong Zhang 059; Ji Liu 003; Juncheng Jia; Yang Zhou 001; Huaiyu Dai; Dejing Dou (IJCAI, 2022)

Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond. - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xuanyu Wu; Xiao Zhang 001; Ji Liu 003; Jiang Bian 003; Dejing Dou (Knowl. Inf. Syst., 2022)

From distributed machine learning to federated learning: a survey. - Ji Liu 003; Jizhou Huang; Yang Zhou 001; Xuhong Li 002; Shilei Ji; Haoyi Xiong; Dejing Dou (Knowl. Inf. Syst., 2022)

Character-Level Street View Text Spotting Based on Deep Multisegmentation Network for Smarter Autonomous Driving. - Chongsheng Zhang; Yuefeng Tao; Kai Du; Weiping Ding 001; Bin Wang 062; Ji Liu 003; Wei Wang 012 (IEEE Trans. Artif. Intell., 2022)

Two-Phase Scheduling for Efficient Vehicle Sharing. - Ji Liu 003; Carlyna Bondiombouy; Lei Mo; Patrick Valduriez (IEEE Trans. Intell. Transp. Syst., 2022)

Knowledge Distillation with Attention for Deep Transfer Learning of Convolutional Networks. - Xingjian Li 002; Haoyi Xiong; Zeyu Chen; Jun Huan; Ji Liu 003; Cheng-Zhong Xu 001; Dejing Dou (ACM Trans. Knowl. Discov. Data, 2022)

Quality-Aware Self-Training on Differentiable Synthesis of Rare Relational Data. - Chongsheng Zhang; Yaxin Hou; Ke Chen 004; Shuang Cao; Gaojuan Fan; Ji Liu 003 (AAAI, 2023)

Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising. - Miaoyu Li; Ji Liu 003; Ying Fu 001; Yulun Zhang 001; Dejing Dou (CVPR, 2023)

LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising. - Zichun Wang; Ying Fu 001; Ji Liu 003; Yulun Zhang 001 (CVPR, 2023)

Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization. - Tianshi Che; Ji Liu 003; Yang Zhou 001; Jiaxiang Ren 001; Jiwen Zhou; Victor S. Sheng; Huaiyu Dai; Dejing Dou (EMNLP, 2023)

Path Planning Based on Traffic Flow Prediction for Vehicle Scheduling. - Yiming Zhao; Lei Mo; Ji Liu 003 (ICCC, 2023)

Pixel Adaptive Deep Unfolding Transformer for Hyperspectral Image Reconstruction. - Miaoyu Li; Ying Fu 001; Ji Liu 003; Yulun Zhang 001 (ICCV, 2023)

Multimodal Biological Knowledge Graph Completion via Triple Co-Attention Mechanism. - Derong Xu; Jingbo Zhou; Tong Xu 001; Yuan Xia; Ji Liu 003; Enhong Chen; Dejing Dou (ICDE, 2023)

Fast Federated Machine Unlearning with Nonlinear Functional Theory. - Tianshi Che; Yang Zhou 001; Zijie Zhang 001; Lingjuan Lyu; Ji Liu 003; Da Yan 001; Dejing Dou; Jun Huan (ICML, 2023)

FT-topo: Architecture-Driven Folded-Triangle Partitioning for Communication-efficient Graph Processing. - Xinbiao Gan; Guang Wu; Ruigeng Zeng; Jiaqi Si; Ji Liu 003; Daxiang Dong; Chunye Gong; Cong Liu; Tiejun Li (ICS, 2023)

Multi-Temporal Relationship Inference in Urban Areas. - Shuangli Li; Jingbo Zhou; Ji Liu 003; Tong Xu 001; Enhong Chen; Hui Xiong 001 (KDD, 2023)

G-LIME: Statistical learning for local interpretations of deep neural networks using global priors. - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xiao Zhang 001; Ji Liu 003; Haiyan Jiang; Zeyu Chen; Dejing Dou (Artif. Intell., 2023)

Large-scale knowledge distillation with elastic heterogeneous computing resources. - Ji Liu 003; Daxiang Dong; Xi Wang; An Qin 001; Xingjian Li 002; Patrick Valduriez; Dejing Dou; Dianhai Yu (Concurr. Comput. Pract. Exp., 2023)

Distributed and deep vertical federated learning with big data. - Ji Liu 003; Xuehai Zhou; Lei Mo; Shilei Ji; Yuan Liao; Zheng Li; Qin Gu; Dejing Dou (Concurr. Comput. Pract. Exp., 2023)

Data Placement for Multi-Tenant Data Federation on the Cloud. - Ji Liu 003; Lei Mo; Sijia Yang; Jingbo Zhou; Shilei Ji; Haoyi Xiong; Dejing Dou (IEEE Trans. Cloud Comput., 2023)

Multi-Job Intelligent Scheduling With Cross-Device Federated Learning. - Ji Liu 003; Juncheng Jia; Beichen Ma; Chendi Zhou; Jingbo Zhou; Yang Zhou 001; Huaiyu Dai; Dejing Dou (IEEE Trans. Parallel Distributed Syst., 2023)

HeterPS: Distributed deep learning with reinforcement learning based scheduling in heterogeneous environments. - Ji Liu 003; Zhihua Wu; Danlei Feng; Minxu Zhang; Xinxuan Wu; Xuefeng Yao; Dianhai Yu; Yanjun Ma; Feng Zhao; Dejing Dou (Future Gener. Comput. Syst., 2023)

G-LIME: Statistical Learning for Local Interpretations of Deep Neural Networks Using Global Priors (Abstract Reprint). - Xuhong Li 002; Haoyi Xiong; Xingjian Li 002; Xiao Zhang 001; Ji Liu 003; Haiyan Jiang; Zeyu Chen; Dejing Dou (AAAI, 2024)

FedASMU: Efficient Asynchronous Federated Learning with Dynamic Staleness-Aware Model Update. - Ji Liu 003; Juncheng Jia; Tianshi Che; Chao Huo; Jiaxiang Ren 001; Yang Zhou 001; Huaiyu Dai; Dejing Dou (AAAI, 2024)

Fisher Information-based Efficient Curriculum Federated Learning with Large Language Models. - Ji Liu 003; Jiaxiang Ren 001; Ruoming Jin; Zijie Zhang 001; Yang Zhou 001; Patrick Valduriez; Dejing Dou (EMNLP, 2024)

AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices. - Ji Liu 003; Tianshi Che; Yang Zhou 001; Ruoming Jin; Huaiyu Dai; Dejing Dou; Patrick Valduriez (SDM, 2024)

Efficient asynchronous federated learning with sparsification and quantization. - Juncheng Jia; Ji Liu 003; Chendi Zhou; Hao Tian 008; Mianxiong Dong; Dejing Dou (Concurr. Comput. Pract. Exp., 2024)

On mask-based image set desensitization with recognition support. - Qilong Li; Ji Liu 003; Yifan Sun; Chongsheng Zhang; Dejing Dou (Appl. Intell., 2024)

Enhancing trust and privacy in distributed networks: a comprehensive survey on blockchain-based federated learning. - Ji Liu 003; Chunlu Chen; Yu Li; Lin Sun; Yulun Song; Jingbo Zhou; Bo Jing; Dejing Dou (Knowl. Inf. Syst., 2024)

Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data. - Ji Liu 003; Juncheng Jia; Hong Zhang 059; Yuhui Yun; Leye Wang; Yang Zhou 001; Huaiyu Dai; Dejing Dou (ACM Trans. Intell. Syst. Technol., 2024)

SGDPO: Self-Guided Direct Preference Optimization for Language Model Alignment. - Wenqiao Zhu; Ji Liu 003; Lulu Wang; Jun Wu; Yulun Zhang 001 (ACL (Findings), 2025)

Latent Diffusion Enhanced Rectangle Transformer for Hyperspectral Image Restoration. - Miaoyu Li; Ying Fu 001; Tao Zhang 042; Ji Liu 003; Dejing Dou; Chenggang Yan 001; Yulun Zhang 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Trustworthy federated learning: privacy, security, and beyond. - Chunlu Chen; Ji Liu 003; Haowen Tan; Xingjian Li 002; Kevin I-Kai Wang; Peng Li 017; Kouichi Sakurai; Dejing Dou (Knowl. Inf. Syst., 2025)

Efficient Federated Learning with Timely Update Dissemination. - Juncheng Jia; Ji Liu 003; Chao Huo; Yihui Shen; Yang Zhou 001; Huaiyu Dai; Dejing Dou (CoRR, 2025)

Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout. - Ji Liu 003; Beichen Ma; Qiaolin Yu; Ruoming Jin; Jingbo Zhou; Yang Zhou 001; Huaiyu Dai; Haixun Wang; Dejing Dou; Patrick Valduriez (CoRR, 2025)

A Systematic Review on Long-Tailed Learning. - Chongsheng Zhang; George Almpanidis; Gaojuan Fan; Binquan Deng; Yanbo Zhang; Ji Liu 003; Aouaidjia Kamel; Paolo Soda; João Gama 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)